Date Posted:2026-06-18
Country:United States of America
Location:US-CT-EAST HARTFORD-RTRC L ~ 411 Silver Ln ~ RTRC L
Position Role Type:Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements: U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
Security Clearance Type: None/Not Required
Security Clearance Status: Not Required
The Dynamics, Control, and Autonomy Team, part of the Intelligent & Cyber-Physical Systems Department at RTX Technology Research Center (RTRC) is looking for a highly motivated individual for the position of research engineer specialized in Learning for Dynamics and Control.
RTRC serves as the innovation hub for RTX. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners and subject matter experts collaborate and exchange experience. We transform that research into the solutions and products that help our businesses shape the future. We are:
- Empowering innovation among the company's businesses.
- Solving customers' critical problems.
- Developing breakthroughs for a safer, more connected world.
- Working with major universities and national laboratories on groundbreaking research.
The Dynamics, Controls, and Autonomy team supports dynamical system analysis and modeling, control system analysis and design, and autonomous systems research for all RTX business units, including both development of novel solutions for future products and solving the toughest problems with current products. In parallel, we are working with government customers on more broadly applicable technology.
What You Will Do- Design and develop novel control solutions for aerospace and defense applications including, but not limited to, jet engines, missiles, autonomous vehicles and systems, avionics, aircraft power systems and air management, hypersonic vehicles, advanced manufacturing, and space systems;
- Work in a multidisciplinary setting, bringing system-level perspective to new cutting-edge technologies from multiple fields (autonomy, power systems, cyber security, mechanical systems, aerodynamics, thermal management)
- Lead and support externally and internally sponsored programs, write external and internal research proposals;
- Disseminate research results through reports, conference proceedings, and peer-reviewed articles, and developing intellectual property.
What You Will Learn- How to transition novel concepts from early technology stages to a state that impacts and influences our products, which in turn have global impact on society
- How to build relationships both within our company, and externally with industry, academia, and government agencies for long-term impact
Qualifications You Must Have- Ph.D. in Mathematics, Physics, Computer Science or Engineering.
- Strong fundamentals in control:
- standard multivariable control and estimation techniques (e.g., LQR/LQG, Kalman filters, optimization-based control, including Model Predictive Control), from formulating the problem to implementation in software
- Experience with machine learning for control, including
- Reinforcement Learning (RL) for safety-critical systems (e.g., model-based RL, Sim2Real transfer learning, or safety guarantees using Control Barrier Functions)
- Verification & Validation of AI/ML control laws
- Neural-network representations of controllers and estimators (e.g., Physics-Informed Neural Networks for MPC, or Neural Network based MPC)
- Control-oriented modeling of physical systems, both from first principles and data-driven (including learning-based methods such as Physics-Informed Neural Networks)
- Proficiency in MATLAB/Simulink, Python, Pytorch or TensorFlow
Qualifications We Prefer - Master degree in Mathematics, Physics, Computer Science or Engineering with minimum 5 years of full-time industrial experience .
- Novel approaches for safety including Control Barrier Functions (CBF)
- Hardware-in-the-Loop validation and real-time/embedded implementation of control laws
- experience with Speedgoat, dSPACE, or LabView/NIDAQ
- FPGA programming
- C/C++ programming
- Experience with multi-agent collaborative autonomy, including
- Multi-agent autonomous behaviors
- Decentralized mission planning and execution
- Hands-on experience with implementation of autonomy algorithms in high-fidelity simulations and/or hardware platforms:
- PX4 or ArduPilot autopilots and software-in-the-loop simulations
- Robot Operating System (ROS, ROS2) and Gazebo simulation
- Open-source planning and perception software packages
- Commercial UAV and UGV platforms
- Experience with one or more of the following technical areas:
- Neural and symbolic AI approaches for course of action development
- Resilient contingency management for multi-agent autonomous systems
- Human-robot teaming
- Application experience in one or more of the following:
- Manufacturing and inspection operations
- autonomous systems, including assurance for autonomy
- safety and certification in aerospace
- gas turbine engine modeling and control;
- Guidance, Navigation, and Control (aircraft, spacecraft, or missiles)
- hypersonic propulsion;
- electric or hybrid-electric propulsion for aircraft;
- control co-design
- Experience with Large Language Models and agentic control
- Experience with writing proposals for government-funded research, record of grants
- a record of innovation as evidenced by patent applications, a track record of writing proposals for government funded research programs, and/or high-quality journal and conference publications.
- Active Security Clearance
Additional Skills and Abilities- Strong analytical, problem-solving and interpersonal skills with track record of teamwork, adaptability, innovation and initiative
- Clear and effective communication with all levels of management, business development, researchers and customers
- Ability to focus on results in a fast-paced, dynamic team environment
- Ability to work independently with limited direction and in multidisciplinary environment to accomplish project goals
- The preferred candidate will look at open-ended tough problems as an opportunity to innovate and develop novel solutions
Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:
Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.
Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee's personal responsibility.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
